Informational efficiency and rational bubbles

This paper develops an approach for reevaluating informational efficiency and financial bubbles by integrating information-theoretic measures with econometric testing. I introduce a generalized entropy model, establish its properties, and illustrate its application in financial markets, particularly its adaptability in handling risk aversion and encapsulating distributional characteristics. The empirical analysis employs approximate and sample entropy to capture the information content of financial time series with explosive roots. This framework, combined with conventional econometric tests, improves the identification of rational bubbles by quantifying uncertainty and nonlinearity in data. Empirical evidence from the housing market suggests a decline in entropy during bubble phases. I also examine the impact of monetary policy shifts on housing bubbles and demonstrate how alterations in policy instruments can modify the entropy of housing prices in reaction to external shocks. The price-rent ratio's response to yield spread shocks indicates that housing bubbles are prone to collapse as the yield spread widens, with effects that gradually taper off.